The following is a collection of notes about writing papers that should primarily help students working on collaborative papers with me, but potentially also other paper authors who want to improve their papers and stumble upon this page. These notes are compiled based on my experience with writing and reviewing papers in robotics.
The main purpose of a scientific paper is to communicate a research idea; the most effective way to do this is to write the paper so that it has a logical flow. In a way, a good paper tells a story - not in a literary sense, but in the sense of having a well-defined starting point and then ensuring that every statement that is made at a given point follows from what was discussed before. This flow may need to be broken occasionally (for instance, when we include a background section before the section in which a proposed method is described), but it should otherwise be followed, both within sections and between sections, so that the reader has a good reading experience.
Good papers are written well. In technical papers, we don’t necessarily expect perfect language, but bad language is an unwanted distraction from the technical aspects of the work. After all, the main purpose of writing a paper should be to communicate one’s work to the research community, and communication works best if language is used correctly. This includes at least the following aspects:
The motivation of a paper sets the context of the work and should make it possible to understand both why the authors think this problem is relevant and why the reader should like to read the proposed solution to it. Particularly when I review a paper, I am not necessarily working on the exact same line of research that the paper is following, so it is important that the authors make it clear why they believe the problem they address is relevant, and in which exact context.
The purpose of a scientific paper is not just showing what one has done, but also how this fits within the bigger picture of the research field. This requires detailed knowledge of similar work done by other research groups, both recently and in the more distant past.
In this context, it is important to talk about the recency bias. Scientific research is incremental, so it is generally the case that one would discuss recent papers more frequently than old ones; however, older techniques can sometimes get out of fashion even though they contain very useful ideas, so simply focusing on recent work is likely to lead to relevant old literature being missed. Having a broad view of one’s field is thus important for writing related work discussions that are as complete as possible.
The thoroughness of the related work discussion obviously depends on the publication venue. Conference papers are usually short (and have a strict page limit), so the related work discussion has to be very focused, while journal papers are considerably longer, so the related work discussion is expected to be more thorough and detailed.
Technical papers are most helpful when they are both precise and concise; this is best achieved by using an appropriate mathematical formalisation. Including a formal description of a problem is necessary due to various reasons:
In many cases, a paper would build on a well-known general formalisation, which clearly simplifies the task of working with the formalisation, as it is mainly necessary to ensure that notation is used consistently and that entities are used in a way that is consistent with their definitions.
When formalising, it is also important not to over-formalise, namely there should be as much formalisation as necessary for presenting the proposed method, but not more than that. In other words, the purpose of formalisation should not be to impress the reviewers or other researchers, but to explain the proposed method as well as possible so that others can understand it fully and are able to build on it in their own work.
In fields such as robotics, it is generally important to evaluate techniques experimentally in order to demonstrate that they are indeed useful from a practical point of view. The evaluation should, however, be meaningful, namely it should not evaluate aspects of a proposed method that are trivial or theoretically obvious, but should instead focus on aspects that are subject to practical uncertainties and thus require statistical evaluation. If such uncertainties can be excluded from consideration, a use case-based demonstration instead of a full-fledged experimental evaluation may also make sense.
Scientific papers are not, or should not, simply be advertisements for a proposed method. An important part of the scientific process is to be honest about the limitations of one’s own work and discuss those openly. After all, authors are the ones who know their method best - both the positive and the negative aspects thereof - so they are in the best position to talk about this in their paper. A discussion of the limitations also leads naturally to ideas for future work, which can be particularly useful for readers who may want to build on the presented method.
A final element of good papers is the use of diagrams and plots so that they help in understanding important aspects of the proposed method.
When reviewing papers, I generally try to see if the above elements are included in the paper, and to what extent. I particularly try to answer the following questions in my reviews:
When reviewing papers, I always try to look for positive aspects that would make the work publishable; however, as a paper reviewer, my job is to also scrutinise the paper in order to ensure that a high scientific standard is maintained. There are thus a few cases in which I have no other choice but to suggest paper rejection. The following are the primary ones: